十进制类型最多有38位。实际上Spark docs中没有提到它，但是在尝试创建更大精度的类型时会出现错误。Databricks docs明确说明了这一点。
尽管如此，38位数仍允许您存储和安全地添加126位（log2(10^38)）数字。

val df = Seq(
  "123456789012345678901234567890",
  "1",
  "100000100000100000100000100001"
).toDF("x")

df.withColumn("x", $"x".cast(new DecimalType(38))).agg(sum($"x")).show(false)
+------------------------------+
|sum(x)                        |
+------------------------------+
|223456889012445679001234667892|
+------------------------------+

如果你需要更多，你可以创建一个custom aggregate function操作字符串。

import org.apache.spark.sql.{Encoder, Encoders}
import org.apache.spark.sql.expressions.Aggregator

object BigSum extends Aggregator[String, String, String] {
  def zero: String = "0"
  def reduce(buffer: String, x: String): String = (BigInt(buffer) + BigInt(x)).toString
  def merge(b1: String, b2: String): String = (BigInt(b1) + BigInt(b2)).toString
  def finish(b: String): String = b
  def bufferEncoder: Encoder[String] = Encoders.STRING
  def outputEncoder: Encoder[String] = Encoders.STRING
}

val big_sum = udaf(BigSum)
df.agg(big_sum($"x")).show(false)
+------------------------------+
|bigsum$(x)                    |
+------------------------------+
|223456889012445679001234667892|
+------------------------------+

PS.我的BigSum不是超级有效的，由于来回转换，它会更好地有缓冲区作为BigInt -我只是不知道如何写编码器[BigInt]...